AllianceChicago is a unique organization. A federally funded health center network of more than 76 community health centers operating in more than 23 states, its work is centered on improving personal, community and public health through innovative collaboration.
The collaboration has been in operation for more than 25 years and is committed to developing and implementing systems that promote equity and optimize health and wellbeing.
It does this by supporting the development and optimal use of health information technology, conducting rigorous community-based research and evaluation, as well as cultivating innovative partnerships with community health centers and stakeholders to explore new ways to promote the health of individuals and communities.
CHCs are ahead of the rest of the healthcare world in understanding the impact of social determinants of health and applying the knowledge in support of the communities they serve. Andrew Hamilton, RN, CIO and deputy director of AllianceChicago, and his team have, for example, partnered with the National Association of Community Health Centers to develop a tool called PRAPARE, which is used by most of the CHCs across the U.S.
Healthcare IT News spoke with Hamilton to discuss a variety of issues from which all provider organizations can learn. We talked about how healthcare information technology helps foster equity, the role of healthcare-generated data in supporting public health surveillance, and the collection and use of social care needs data.
Q. Equity in healthcare is a huge and important issue to be tackled. How can healthcare information technology help foster equity?
A. The IOM [now the National Academy of Medicine] outlined six domains of quality in healthcare, where health information technology can play a key role: safe, effective, patient-centered, timely, efficient and equitable.
It is widely understood that health IT is a critical aspect relative to each of these domains of healthcare. With respect to health IT and equity, the techquity framework provides an approach to the strategic design, development and deployment of technology to advance health equity. It encompasses the notion that technology can either support or inhibit advancements in health equity if not implemented in an intentional and inclusive manner.
It is also important to note that techquity is not an “individual or consumer-level” problem. Rather, promoting or advancing techquity will require collaboration, transparency, inclusivity, and a commitment to ensure organizational transformation at a systemic level to achieve equitable care.
Three key elements of health IT are necessary to optimize technology to promote equity in care: unencumbered access, use (uptake and usability), and sustained engagement. These factors that impact techquity are highly correlated to health-related social needs including (but not limited to) access to the internet/broadband services, affordability of technology services and tools, language accessibility features (beyond English and Spanish), and digital and health literacy.
In other words, the design and deployment of health IT must consider these health-related needs in order to ensure technology to promote equitable care.
Q. Public health is a key issue for everyone in healthcare to support. What is the role of healthcare-generated data in supporting public health surveillance?
A. The COVID pandemic highlighted several opportunities to strengthen both our healthcare delivery system and our public health infrastructure. With respect to surveillance, the public health system in the U.S. was largely informed by vital records (birth/death certificates, mandatory case reports, laboratory data), survey data (consumers, healthcare providers, insurance companies), environmental monitoring (water and air quality), and animal health (veterinarians, farms and food manufacturers).
A key issue in each of these domains is the timeliness, consistency and interoperability of the information. These factors significantly impact the total time to access, process and analyze these data, which inhibits a timely and coordinated public health response, particularly during a novel disease outbreak.
With respect to electronic health systems, there is a clear opportunity to modernize the public health surveillance infrastructure, particularly with advancements in data standardization and interoperability which underpin the 21st Century Cures Act, which, in part, regulates EHR systems.
AllianceChicago, in partnership with the National Association of Chronic Disease Directors as well as other partners, has recently completed a five-year CDC-funded demonstration project that established an EHR disease surveillance system to both inform public health surveillance as well as demonstrate how a shared system between public health and healthcare delivery can improve the monitoring, coordination of public health surveillance and response.
There have been similar efforts demonstrating the use of EHR data to support public health including pediatric obesity, sexually transmitted infections and maternal health outcomes. It is clear from all of these programs that EHR data is a vital and rich asset to support public health surveillance.
I believe the critical next phase of work will be to harmonize these efforts as well as develop a pathway to scale these networks to incorporate additional data contributors in order to ensure adequate and equitable representation of the U.S. population as well as incorporate data sources related to social drivers of health.
Q. You’re keen on addressing social care needs. Please discuss the collection and use of social care needs data.
A. In both of my previous responses, it is clear that to develop a person-centered, equitable healthcare delivery system (including public health system) it is critical to collect, analyze and develop coordinated responses to social care needs as an important aspect of improving health outcomes and equity.
In terms of collecting social care needs data, there is growing evidence that a “mixed-methods” approach is needed; meaning directly collect information from those receiving care as well as use population-level social care needs data (for example, risk indices).
The challenge with individually collected social care needs data is that it is often a “snapshot” of the individual (collected when the person is engaged in care) and therefore as the individual circumstances change over time the point and time data may misrepresent the need.
That said, population-level social care needs data is an estimate of those in the population of focus and therefore can over- or under-estimate an individual’s needs. In addition to data collection issues, work is underway to standardize these data to ensure comparability and interoperability of the data.
The standardization work, such as the work of Gravity Project, is critical to ensure data can be processed, analyzed and shared in a consistent and meaningful manner. Collection and standardization of the data are critical components to ensure optimal and effective use of the data.
At the individual level, a significant use of social care needs data is related to the incorporation of social care needs into the patient’s overall plan of care. Our understanding of the most effective and efficient way to use these data in developing a plan of care is evolving.
While we have a great deal to learn, we have several examples from the field including incorporating support for access to housing, food and transportation. Interventions in social care needs often require cross-sector data sharing and collaboration, which also require system- and community-level change, which are challenging.
In addition to the individual level use of these data, health systems are learning how to use these data at a population level, which is critical both in terms of improving overall outcomes and health equity. Finally, the relationship between population health and public health provides a clear opportunity to coordinate health system-level interventions with public health programs.
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Healthcare IT News is a HIMSS Media publication.